改进的粒子群算法及在数值函数优化中应用

为提高粒子群算法的优化能力,提出了一种改进的粒子群优化算法。在该算法中,采用Beta分布初始化种群,采用逆不完全伽马函数更新惯性权重,在速度更新式中,引入了基于差分进化的新算子,对于粒子的越界处理,采用了基于边界对称映射的新方法。以50个不同类型的数值函数作为优化实例,基于威尔柯克斯符号秩检验的测试结果表明,该算法明显优于普通粒子群优化算法、差分进化算法、人工蜂群优化算法和量子行为粒子群算法。     

SA-PSO算法在CNN边缘提取模板设计中的应用

提出了一种用于边缘提取的细胞神经网络（CNN）模板的设计方法,该方法在基本粒子群算法的基础上引入模拟退火机制,形成模拟退火粒子群算法（SA-PSO）对模板参数值进行搜寻。在搜索过程中,用退火温度调节粒子的突跳概率,轮盘赌策略确定粒子的全局最优的替代值,这样能有效避免基本PSO算法容易陷入局部最优解的问题。同时,为了保证每轮搜寻产生的解均能使CNN网络稳定,用CNN反馈模板的研究结论对粒子群解空间进行约束。模拟实验表明,文章算法设计出的CNN模板有良好的边缘提取能力。     

AN ACCELERATION SEARCH METHOD FOR UNCONSTRAINED OPTIMIZATION AND ITS APPLICATION IN MODEL PARAMETER ESTIMATION

In order to improve the convergence rate of the algorithms, an acceleration search method along a straight or curve is proposed,and the specific calculation steps of the algorithms are presented. The numerical results in model parameter estimation show that the convergence rate is improved and the calculation accords with the practical demands.     

花椰菜主要性状遗传参数的初步研究

应用方差—协方差分析法,研究了花椰莱11个数量性状的遗传力,遗传变异系数,遗传进度及性状间的表现型相关和遗传相关系数,以及在选择单一性状时,单株花球重和成熟期的相关遗传进度,为进一步开展花椰莱育种的研究提供理论依据。     

Structural Optimum of Main Tower- Frame of Mast Crane

Taking the Structural optimum of main metal frame of mast- crane as a sample,this paper discussed the method of Structural optimization of common middle & high flexibility metal tower- frame by dynamic programming.The method of dynamic programming applied to the structural optimum was deducted and the minimum weight design method of tower- frame was practiced The paper gave up the traditional interactive way of choosing type of material,combining with the concrete example,changed the data- table looking up into formula solution,shifting with one by one into directly sieving within selected types,artificially fixing up composed rods into automaticaliy arranging them through the way of maximum twist moment of inertia,thus,accelerate optimization and offered a short way for artificial structural analysis and calculation.     

Application of Evolutionary Programming in Optimal Reactive Power Dispatch

This paper describes an application of evolutionary programming(EP) to reactive power optimization and voltage control of power systems.Some technical problems which conclude mutation sacle,fitness value and population size have been solved to make EP practical for solving the optimal power flow problems.The computational results with EP have been compared with those obtained from a conventional gradient based optimization method.The comparision shows that EP are better than conventional methods in dealing with the optimization of noncontinuous and nonsmooth funcnons.The EP show the ability to search for the global optimum in reactive optimization that has multiple optima.     

基于区间分析的框架结构不确定性损伤识别方法

考虑实际结构易受荷载、环境温度和测试噪声等不确定性因素的影响,笔者基于区间分析原理提出框架结构不确定性损伤识别方法。利用测试的结构加速度响应数据,建立向量自回归模型,并采用其系数矩阵主对角线的马氏距离作为损伤特征指标。基于粒子群算法建立区间优化求解方法,并与传统的区间组合法和区间叠加法对比。通过提出的区间重叠率指标和区间名义值分别实现损伤定位和损伤程度的识别。数值模拟和实验室框架结构试验结果表明,区间分析能在测试数据较少时实现损伤识别,为损伤识别在实际结构中的应用提供了理论基础和技术手段。     

基因枪转化小麦主要轰击参数的优化

基因枪转化是目前小麦遗传转化的主要方法。影响基因枪转化效率的主要参数有轰击距离、轰击压力、DNA总量及浓度、金粉颗粒大小及用量等。为改善目前小麦遗传转化效率偏低的现状, 以普通小麦品种科农199为受体材料, 设金粉大小(0.6 μm和1.0 μm)、轰击距离(5.5 cm和8.5 cm)及轰击压力(650、900和1100 psi)三因素共12个处理, 利用pAHC25质粒转化小麦幼胚, 以确定最佳轰击参数, 建立稳定高效的普通小麦基因枪转化体系。结果表明, 3个因素的不同组合对幼胚的愈伤诱导效率没有明显影响, 但对再生率影响较大, 以金粉0.6 μm、轰击距离5.5 cm的再生率最高。3个因素组合的不同处理对GUS瞬时表达有明显影响, 以金粉0.6 μm、轰击距离5.5 cm和轰击压力650 psi处理的GUS瞬时表达量最高。本试验最终获得28株转基因植株, 其中12株来自金粉0.6 μm、轰击距离5.5 cm和轰击压力650 psi的处理, 该处理的平均转化率达2.66%。     

Cylindricity error evaluation using artificial bee colony algorithm with tabu strategy

For cylindricity error evaluation, the Least Squares Method (LSM) is not good enough because of the big error, while the bionics algorithms such as Genetic and Ant Colony Algorithm need to set many parameters and converge slowly, an Artificial Bee Colony Optimization Algorithm is proposed to evaluate the minimum zone cylinder (MIC). This Algorithm refers the tabu strategy for tabu search algorithm to use the Tabu table to save the local optimization results. It enhances the control effect of parameter limit and improves the global convergence ability. Experiment results indicate that this method can converge to the global optimization very quickly. The average runtime is nearly 1.2 s. It is applicable to the real time processing system such as Three Coordinate Measuring Machine.     

往复式切割器传动机构运动动力学分析

油菜收获机割台损失主要由割台振动与割刀切割损失两部分形成,而割台上的往复式切割器工作时的惯性冲击力是造成其振动损失的主要因素之一。为降低油菜联合收割机割台损失,本文对油菜联合收割机上往复式切割器传动机构进行了运动动力学分析,建立了该机构运动动力学模型,分析了各主要构件的运动加速度,得到了求解机构中各运动副之间约束力的方程组,并对方程组进行了求解,得到了主要构件的惯性力表达式。在此基础上分析了惯性力的影响因素。其研究结论为降低往复式切割器惯性冲击力的影响,降低割台振动,优化结构提供了理论依据。     

MDBPSO算法优化的全波段光谱数据协同冠层SIF监测小麦条锈病

为了从全波段光谱数据中提取对小麦条锈病敏感的特征参量,提高小麦条锈病遥感探测模型的运行效率和精度,本文首先从惯性权重和粒子更新方式两个方面对传统离散粒子群算法(discretebinaryparticleswarmoptimization, DBPSO)进行改进,利用改进离散粒子群算法(modified discrete binary particle swarm optimization, MDBPSO)从全波段光谱数据中优选遥感探测小麦条锈病严重度的特征变量,然后与冠层日光诱导叶绿素荧光(solar-inducedchlorophyllfluorescence,SIF)数据相结合作为自变量分别利用随机森林(randomforest,RF)和后向传播(backpropagation,BP)神经网络算法构建小麦条锈病遥感探测模型,并将其与相关系数(correlationcoefficient,CC)分析法和DBPSO算法提取特征参量构建模型的精度进行对比分析。结果表明:(1) MDBPSO算法比传统DBPSO算法具有更快的收敛速度和更高的寻优精度,改进前后其迭代次数从395次减少到156次,最优适应度函数(optimumfitnessvalue,OFV)值从0.145减小到0.127。(2)采用MDBPSO算法选择特征变量时,RF和BP神经网络两种方法构建的模型精度均高于CC分析法和DBPSO算法,其中RF算法预测病情指数(diseaseindex,DI)值和实测DI值间的检验集决定系数(validation set determination coefficient, R2V)比CC分析法和DBPSO算法分别提高了9%和3%,均方根误差(validation set root mean square error, RMSEV)分别降低了28%和11%, BP神经网络算法预测DI值和实测DI值间的R2V比CC分析法和DBPSO算法分别提高了13%和6%,RMSEV分别降低了21%和10%,利用MDBPSO算法优选特征参量能够提高小麦条锈病的遥感探测精度。(3)在MDBPSO、DBPSO和CC分析法3种特征选择算法中,RF算法构建的模型精度均高于BP神经网络算法,其中RF模型预测DI值和实测DI值间的R2V比BP神经网络算法至少提高了7%,平均提高了9%,RMSEV至少降低了15%,平均降低了20%。以MDBPSO算法优选的特征参量为自变量利用RF方法构建的小麦条锈病遥感探测的MDBPSO-RF模型是小麦条锈病遥感探测适宜模型,该研究结果为进一步实现作物健康状况大面积高精度遥感监测提供了新的思路。     

Effects of Wave Speed on Frequencies of the Self excited Oscillation Pulsed Abrasive Water Jets

The effects of cavitation and abrasive acceleration in the self excited oscillation pulsed abrasive water jets are directly determined by its oscillating frequencies, so the wave speed in the jets and its effects on pulsed frequencies are discussed. The numerical results show that the oscillating frequencies of the jets increase obviously with decreasing wave speed, and the abrasive parameters have almost no effects on the wave speed, whereas the exit of air in fluid has significant consequences on the wave speed.It was found that these conclusions were applicable for design the nozzle of the jets.     

Application of a Particle Swarm Optimization Algorithm in Truss Structure Optimal Design

The particle swarm optimization (PSO) algorithm developed in recent years is a stochastic optimization algorithm based on swarm intelligence. It possesses advantages such as being a simple concept, ease of implementation and low resource occupation. The PSO algorithm was adopted to solve the problem of size optimization of truss structures with stress and displacement constraints. We present the basic principle of the original PSO algorithm in detail, and then introduce a constriction coefficient to modify it. Moreover, reasonable values of the coefficients are proposed for the modified PSO algorithm. Several classical problems are solved using the modified PSO algorithm, and the results compared with those using traditional optimization algorithms and genetic algorithms. Numerical results show that the modified PSO algorithm has good convergence and stability, and can be applied to the size optimization of truss structures.     

A novel shuffled frog leaping algorithm for ICPT power programming

A new mode of inductively coupled power transfer (ICPT) is presented to city electrization traffic vehicle power supply optimization. The power supply distribution plan and ICPT technology are investigated. To avoid the local optimal of shuffled frog leaping algorithm (SFLA),a novel algorithm based on mutative scale chaos search and SFLA is presented. It is applied to inductively coupled power transfer substation optimal planning. The advantages of global and local search strategies for SFLA are combined with the proposed algorithm. In order to implement local refined search to improve local chaotic search ability and to enhance the solution accuracy, mutative scale chaos search is introduced to the proposed algorithm. The minimum annual expense of the proposed algorithm is 2.39% less than that of SFLA, which shows its advantage.     

Chaotic Synchronization of Discrete Nonlinear Systems on Different Parameters for a Kind of Systems

According to the theory of parameters adaptive control and variable driving, for a kind of discrete nonlinear chaotic systems, a method of chaotic synchronization is presented for different system parameters. In the equation of parameters adaptive control, control coefficients are chaotic signal. Because control coefficients are constant usually for the former parameters adaptive control, so the parameters adaptive control method is very universal, namely the former parameters adaptive control methods are special examples in our control method. Simulation results show that this method is available.     

Job-Shop scheduling based on improved immune cloning algorithm

Parallel immune clone algorithm is proposed based on population coevolution theory and parallel computing affinity of individual at multiple compute nodes. Introducing the immune memory mechanism, the evolution processes of antibody population and memory units are conducted simultaneously, meanwhile, it improves mutual cooperation among antibodies, and ensures solution set approaching optimal solution from the inside of feasible region or infeasible region border. Clone proliferation, high frequency variation and operation of crossover operators increase the chance that better individuals gain affinity maturation by the operation of clone expansion, improve diversity of antibody population distribution, achieve the balance of optimization between depth and range, and ensure the convergence of the algorithm and the diversity of the search range. A computational study for a standard data set is carried out to test the validity of the algorithm, and the effect of algorithm parameters on the results is analyzed. The simulation results show that the global search capability, local search capability, algorithm stability and computing speed of the algorithm are all superior to conventional optimization algorithms such as normal immune clone optimization algorithm, genetic algorithm, etc.     

Research on Sustainable Exploration of the Geothermal Water in Nanwenquan Anticline of Chongqing

The geothermal water of Nanwenquan,Xiaoquan and Qiaokouba is a whole geothermal water system in Nanwenquan anticline of Chongqing.In the past,due to lack of study on sustainable exploration of the geothermal water,the source of geothermal water from Nanwenquan and Xiaoquan was drying up.Now,three enterprises are exploiting the geothermal water in Qiaokouba.There must be a sustainable exploration for the geothermal water,in order to utilize and protect the geothermal water resource.The geothermal water in the three exploiter's areas was quantitatively studied on sustainable exploitation by finite element numerical simulation.The geological mode was generalized and the mathematical model was established.Then,the simulative water level obtained was compared with the actual one,and the mathematical model was identified and adjusted.The right mathematical model has been acquired when the simulative water level obtained was approximate to actual water level.The infiltration of geothermal water was simulated under two schemes of exploitation conditions.An optimum scheme has been obtained by analysis.The maximal yield of exploitation was acquired under sustainable exploitation of the geothermal.     

棉花不同铃重类型种质主要纤维性状遗传及其变异

以中棉所48的母本S9708与不同铃重大小的父本杂交,配置6个F2群体,采用SAS 8.0软件对各组合亲本、F1和F2的铃重和衣分及纤维品质等数量性状进行统计分析。结果表明:在所有F2群体中纤维性状都有极显著差异。铃重和麦克隆值的变异系数较大,其次是衣分和纤维强度,而纤维长度、伸长率和整齐度变异系数较小。在杂交早代群体中,仍然表现亲本的铃大、衣分高、纤维长、强度高、整齐度好等优良特性。这表明,在杂种优势利用选择亲本时,选择大铃、高衣分、优质纤维材料仍较为重要。     

水稻第5节间长度与出穗促进率的相关性

出穗促进率和株高变化是反映水稻品种光温生态响应的重要指标。能否在育种阶段采用相对容易识别的性状来判断水稻品种的生态响应能力,对广适性品种的选育具有重要意义。本文从12个水稻亲本聚合杂交后代选出的36个高代稳定自交系及其亲本共48份材料,在湖北荆州作中稻以及在广州作早稻和晚稻,研究不同生态条件下株高及各组成成分变化与出穗促进率的变化规律。结果表明,第5节间长度是株高成分中最容易受环境影响的部分,其在不同季节的变化与出穗促进率呈现极显著的正相关性,在早稻和中稻、中稻和晚稻、早稻和晚稻3种情况下,第5节间长度变化和出穗促进率之间的相关系数分别为0.37、0.52和0.49,均达到了极显著水平,偏相关系数分别为0.42、0.43和0.36,也都达到了极显著水平。说明第五节间长度容易受光温条件的影响,是生态响应变化的重要指标,越是敏感的材料响应越大,适应性越差。因此,不同环境条件下第五节间长度可用作判断水稻品种对光温条件的响应指标。     

Plant character correlations and path analysis of pod yield in okra (Abelmoschus esculentus)

Summary Genotypic, phenotypic and environmental correlation coefficients were calculated for fifteen characters during two growing seasons. Correlation coefficients varie between seasons. Edible pod weight, edible pod length, edible pod width, number of seeds per plant, weight of 100 seeds, length of mature pods and number of branches per plant showed significant genotypic correlation with pod yield per plant; only number of branches per plant, edible pod length and weight of 100 seeds were phenotypically correlated with pod yield. Environmental correlation coefficients were generally low but edible pod length, final plant height and edible pod weight showed significant environmental correlation with pod yield during the two seasons.The genotypic correlation coefficients of selected eight characters with pod yield were partitioned into direct and indirect causes. In the early seasons, edible pod weight had the largest positive direct effect on pod yield with its largest indirect effect through reduction in edible pod width. Edible pod width which was highly correlated with pod yield had a negative direct effect on pod yield. In the late season, edible pod weight had the largest direct effect on pod yield, with large indirect effects through reduction in number of days to flowering and number of pods per plant. Number of days to flowering had a large direct effect on pod yield with its largest indirect effect through reduction in edible pod weight. The residual factors during the two seasons were negative. The study indicated that only number of branches per plant, edible pod length and weight of 100 seeds would be useful for indirect selection for pod yield. The path analysis indicated that edible pod weight was the most reliable and effective character to select for when high yield is the objective.